1. Field of the Invention
The present invention relates to Internet searching, and more particularly, to generating topic pages through an algorithm that assembles information from branded source and aggregated source by analyzing a query.
2. Description of the Related Art
With the proliferation of information available on the Internet, the Internet has become an effective search tool. A web application receives a query with one or more keywords or topic identifier. The query is used to find information from one or more web services available to the web application and a plurality of results that apply to the query. In a module based web application, modules are selected in order to bring in appropriate content in response to the query. In cases where the relevant information is from multiple sources, it is extremely crucial to choose the appropriate source to provide the most relevant information. This might involve choosing modules from either the branded source or the un-branded source.
Most of the conventional web applications render greater importance to sponsored contents or contents of branded source that either provides greater immediate monetary returns or are reputable rather than on the actual content that are more relevant to a user's query or the long term returns that could be generated from a returning customer. Accordingly, the conventional web applications rank such content modules higher than the content modules that might be more relevant to the query. As a result, during the rendering of the content modules in the results page, the content modules ranked higher are rendered more prominently while the content modules that satisfy the user's intent but are ranked lower are not rendered at all. This results in a results page that is not optimal to the user's search needs or the long term monetization.
One way of avoiding branded contents is to choose only un-branded modules and generating a webpage using these modules in response to the query. However, by choosing only un-branded contents, one is not guaranteed that the returned content modules are optimal to the query and/or user.
Further, it is hard to select a relevant branded or un-branded source amongst a plurality of branded or un-branded sources that is more relevant to the user for the query. For instance, in case of financial information, it is hard to decide if the module from Wall Street Journal™ is more relevant than a module from CNN™ Finance. Similarly, it is hard to decide if any one un-branded source amongst a plurality of un-branded sources provides more relevant information for a breaking news story, such as Michael Jackson's death. Still further, expected relevant information for a query in one geo location may be different from another geo location. It would, therefore, not be practical to manually tag the topics without considering geo locations or just rely on only branded sources or un-branded sources for content. It is also likely that the branded content that would be most satisfying to one user would not be the most satisfying to another user.
It is in this context that embodiments of the invention arise.